The presently disclosed inventive concepts relate to image analysis, and more specifically to improving workflows that rely on image data as a source of input via adaptively and proactively replacing and/or supplementing inputs for analysis in the course of the workflow.
A plethora of online tools and workflows exist which leverage image data as a source of information for various applications. As mobile devices become an increasingly prevalent mechanism to access online tools, capturing image data and performing such analyses via mobile devices is a useful extension of such workflow solutions.
In addition, as optical sensors embedded with mobile devices become more powerful, a wide variety of image-based technologies are migrating to mobile platforms. Accordingly, some tools for mobile applications include the ability to extract textual information from image data, so long as the textual information depicted in the image data is of sufficient quality to allow conventional extraction techniques, such as optical character recognition (OCR), to accurately recognize the characters of the text.
However, due to limitations inherent to the mobile device, and also the variability of conditions surrounding capturing an image using a mobile device, it is often difficult, or even impossible, to capture an image of sufficient quality to allow conventional extraction techniques to accurately recognize the characters of the text or otherwise complete image processing requisite to advance or complete the workflow. As a result, existing image analysis tools are unable to provide an accurate result in many situations.
Accordingly, it would be beneficial to provide systems and techniques for providing accurate image analysis results even when the image data are of insufficient quality to allow conventional techniques to accurately analyze the image data.